The Web We Weave: Untangling the Social Graph of the IETF

The Web We Weave: Untangling the Social Graph of the IETF
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DOI:
10.1609/icwsm.v16i1.19310
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发表时间:
2022-05
期刊:
2024 10th International Conference on Web Research (ICWR)
影响因子:
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通讯作者:
Prashant Khare;Mladen Karan;Stephen McQuistin;C. Perkins;Gareth Tyson;Matthew Purver;P. Healey;Ignacio Castro
Prashant Khare;Mladen Karan;Stephen McQuistin;C. Perkins;Gareth Tyson;Matthew Purver;P. Healey;Ignacio Castro
中科院分区:
其他
文献类型:
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作者:
Prashant Khare;Mladen Karan;Stephen McQuistin;C. Perkins;Gareth Tyson;Matthew Purver;P. Healey;Ignacio Castro

文献摘要

相似文献

Internet工程任务组(IETF)开发了许多支持Internet的技术标准。IETF遵循的标准制定过程是开放的,由共识驱动的,但本质上是一种社会和政治活动,社区内可能存在潜在的影响结构。探索和理解这些结构对于确保IETF的弹性和开放性至关重要。我们使用网络分析来探索IETF参与者的社交图谱,基于公共电子邮件讨论和合著者关系,以及关键贡献者的影响。我们发现,少数核心参与者占主导地位:前10%的人贡献了近一半(43.75%)的电子邮件,来自相对较小的组织群体。另一方面,我们也发现,随着时间的推移,影响力变得相对更加分散。IETF参与者还提出并制定草案,这些草案要么被工作组采纳以进一步改进,要么在早期阶段被拒绝。使用社交图特征与电子邮件文本特征相结合,我们进行回归分析,以了解用户影响对被IETF采用的新工作成功的影响。我们的研究结果为参与者的行为、影响力与草案通过成功之间的相关性以及附属组织在草案作者身份中的重要性提供了有用的见解。
The Internet Engineering Task Force (IETF) has developed many of the technical standards that underpin the Internet. The standards development process followed by the IETF is open and consensus-driven, but is inherently both a social and political activity, and latent influential structures might exist within the community. Exploring and understanding these structures is essential to ensuring the IETF’s resilience and openness. We use network analysis to explore the social graph of IETF participants, based on public email discussions and co-author relationships, and the influence of key contributors. We show that a small core of participants dominates: the top 10% contribute almost half (43.75%) of the emails and come from a relatively small group of organisations. On the other hand, we also find that influence has become relatively more decentralised with time. IETF participants also propose and work on drafts that are either adopted by a working group for further refinement or get rejected at an early stage. Using the social graph features combined with email text features, we perform regression analysis to understand the effect of user influence on the success of new work being adopted by the IETF. Our findings shed useful insights into the behavior of participants across time, correlation between influence and success in draft adoption, and the significance of affiliated organisations in the authorship of drafts.